Proof pending. This topic has not reached the minimum paper threshold yet.
Causal inference holds immense value in fields such as healthcare, economics, and social sciences. However, traditional causal analysis workflows impose significant technical barriers, requiring resea...
Large Language Models (LLMs) have shown strong potential as conversational agents. Yet, their effectiveness remains limited by deficiencies in robust long-term memory, particularly in complex, long-te...
Long-term conversational agents must decide which turns to store in external memory, yet recent systems rely on autoregressive LLM generation at every turn to make that decision. We present MemRouter,...
Large Language Model-powered conversational agents (CAs) are increasingly capable of projecting sophisticated personalities through language, but how these projections affect users is unclear. We thus...
Freshness
Canonical route: /topics
Agent Handoff
Canonical ID conversational-agents | Route /topic/conversational-agents
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/topic/conversational-agentsMCP example
{
"tool": "search_papers",
"arguments": {
"query": "Conversational Agents",
"cluster": "Conversational Agents"
}
}source_context
{
"surface": "topic",
"mode": "topic",
"query": "Conversational Agents",
"normalized_query": "conversational-agents",
"route": "/topic/conversational-agents",
"paper_ref": null,
"topic_slug": "conversational-agents",
"benchmark_ref": null,
"dataset_ref": null
}Use This Via API or MCP
Topic pages bundle paper counts, viability trends, author concentration, and top questions into one canonical surface your agents can reference before they open Signal Canvas or create a workspace.